Protein contact map refinement for improving structure prediction using generative adversarial networks | Zendy

Sai Raghavendra Maddhuri Venkata Subramaniya | Zendy; Genki Terashi | Zendy; Aashish Jain | Zendy; Yuki Kagaya | Zendy; Daisuke Kihara | Zendy

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Protein contact map refinement for improving structure prediction using generative adversarial networks

Author(s) -

Sai Raghavendra Maddhuri Venkata Subramaniya,

Genki Terashi,

Aashish Jain,

Yuki Kagaya,

Daisuke Kihara

Publication year - 2021

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btab220

Subject(s) - generative grammar , computer science , generative adversarial network , adversarial system , artificial intelligence , machine learning , deep learning

Protein structure prediction remains as one of the most important problems in computational biology and biophysics. In the past few years, protein residue-residue contact prediction has undergone substantial improvement, which has made it a critical driving force for successful protein structure prediction. Boosting the accuracy of contact predictions has, therefore, become the forefront of protein structure prediction.

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